research-article

Forest fire modeling and analysis based on K-means clustering algorithm and time series forecasting

Authors:

Yuanwei Li,

Sikui Zhang,

Guoyi FuAuthors Info & Claims

BIC '22: Proceedings of the 2022 2nd International Conference on Bioinformatics and Intelligent Computing

Pages 310 - 316

https://doi.org/10.1145/3523286.3524560

Published: 31 May 2022 Publication History

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BIC '22: Proceedings of the 2022 2nd International Conference on Bioinformatics and Intelligent Computing

Forest fire modeling and analysis based on K-means clustering algorithm and time series forecasting

Pages 310 - 316

Abstract
References

Abstract

Since September 2019, forest fire incidents have broken out in several states in southeastern Australia, forming hundreds of fire points. Many fire incidents are rampant, smoky, and harmful. The theme of this paper is how to use specific drones to quickly monitor and eliminate forest fire incidents in Victoria. First, the K-means clustering algorithm is used to divide the fire point dataset into 4 partitions. Next, we model a multi-objective programming algorithm and solve the shortest distance for the drone to traverse all fire sample points in each partition by the ant colony algorithm, and get the lowest cost purchase plan for SSA drones and Radio Repeater drones. And we model a time series forecasting algorithm for predicting the number of fire incidents in the next 10 years and obtain the increasing cost of purchasing drones each year correspondingly.

References

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Bowman, D. M., Kolden, C. A., Abatzoglou, J. T., Johnston, F. H., van der Werf, G. R., & Flannigan, M. (2020). Vegetation fires in the Anthropocene. Nature Reviews Earth & Environment, 1(10), 500-515.

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Woodward, C., & Haines, H. A. (2020). Unprecedented long-distance transport of macroscopic charcoal from a large, intense forest fire in eastern Australia: Implications for fire history reconstruction. The Holocene, 30(7), 947-952.

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Sahu VKhan MMadguni O(2024)Assessing forest fire dynamics and risk zones in Central Indian forests: a comparative study of the Khandwa and North Betul forest divisions of Madhya PradeshEnvironmental Monitoring and Assessment10.1007/s10661-024-12960-0196:9Online publication date: 14-Aug-2024
https://doi.org/10.1007/s10661-024-12960-0
Mimboro PKusrini KLaksito A(2022)Spatial Hotspot Data and Weather for Forest Fire Data Clustering2022 5th International Conference on Information and Communications Technology (ICOIACT)10.1109/ICOIACT55506.2022.9971884(160-165)Online publication date: 24-Aug-2022
https://doi.org/10.1109/ICOIACT55506.2022.9971884

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BIC '22: Proceedings of the 2022 2nd International Conference on Bioinformatics and Intelligent Computing

January 2022

551 pages

ISBN:9781450395755

DOI:10.1145/3523286

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 31 May 2022

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BIC 2022: 2022 2nd International Conference on Bioinformatics and Intelligent Computing

January 21 - 23, 2022

Harbin, China

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Sahu VKhan MMadguni O(2024)Assessing forest fire dynamics and risk zones in Central Indian forests: a comparative study of the Khandwa and North Betul forest divisions of Madhya PradeshEnvironmental Monitoring and Assessment10.1007/s10661-024-12960-0196:9Online publication date: 14-Aug-2024
https://doi.org/10.1007/s10661-024-12960-0
Mimboro PKusrini KLaksito A(2022)Spatial Hotspot Data and Weather for Forest Fire Data Clustering2022 5th International Conference on Information and Communications Technology (ICOIACT)10.1109/ICOIACT55506.2022.9971884(160-165)Online publication date: 24-Aug-2022
https://doi.org/10.1109/ICOIACT55506.2022.9971884

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Hybrid Bisect K-Means Clustering Algorithm

Forest fire monitoring and burnt area mapping using satellite data: a study over the forest region of Kerala State, India

A Novel Hybridization of ARIMA, ANN, and K-Means for Time Series Forecasting

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